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Author(s):
Mahdi Makoyo, Balarabe A. Saidu.
Page No : 1-9
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INVESTIGATION OF THE FOUNDRY PROPERTIES OF BACHIRAWA SAND
Abstract
The foundry properties of Bachirawa sand deposit located in Dawakin Tofa Local Government Area of Kano State was investigated. The sourcing of good foundry sand is one of the problems in foundry operations, in most cases foundry sand had to be transported from locations with good quality sand towhere the foundry plants are located.This problem had forced many foundry operators to locate their foundry closer to the source of this very important raw material. Sand samples were collected from the deposit and test specimens were prepared for investigation of foundry properties such as strength, permeability, compactibility, flowability, plasticity, bulk density, collapsibility, refractoriness, grain size etc. The results of the investigation revealed that Bachirawa sand possess the following properties: grain fineness number of 111.76, green compression strength of 90.35kN/m2, green shear strength of 19.3kN/m2, dry compression strength of 4726.5kN/m2, dry shear strength of 531.3kN/m2, permeability of 220Ws, flowability of 98.4%, bulk density of 1.81g/cm3, shattered index of 82.9%, clay content of 12.48%, compactibility of 50.9% and refractoriness between1400oC to 1450oC. The result also revealed that the sand is high silica sand with 80.75% silica, 4.17% alumina, 2.54% iron, 0.11%calcium oxide and 0.03% magnesia. The sand can be considered to be fine sand based on its grain fineness number which is above 100 in ranking of American Foundry Society. Based on the values of the strengths obtained, the sand can be considered good for sand moulding such as sand casting of non-ferrous metal such as aluminum products and cast iron machine components.
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Author(s):
Lawan, I., Ali, M.A, Abubakar, M. S..
Page No : 10-19
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EFFECTS OF SOME EXPERIMENTAL FACTORS ON THE PERFORMANCE OF AN INTEGRATED OIL EXTRACTION MACHINE
Abstract
An integrated groundnut oil extraction machine developed at the Department of Agricultural Engineering, Bayero University Kano was evaluated and the effects of some experimental factors were examined. Throughput capacity, extraction rate and extraction efficiency were used as performance indicators, while varieties of groundnut seeds (Manipintar and Ex-Dakar), kneading speeds on the paste (200, 111 and 73 rpm) and quantities of groundnut seeds (24, 16.8 and 12 kg) were used as experimental factors. The experiment was conducted using 2x3x3 factorial in completely randomized design (CRD) in three (3) replications. Thus, a total of fifty four (54) experiments were conducted with the samples at 2.52 and 2.69% (db) moisture content for Manipintar and Ex-Dakar variety respectively. The oil content of the samples obtained were 50.40 and 49.20% for Manipintar and Ex-Dakar variety respectively. Results revealed that the highest throughput capacity achieved was 24.45 kg/hr with combination of Ex-Dakar Variety, kneading speed of 200 rpm and 24 kg of groundnut seeds. The highest extraction rate achieved was 7.90 Lit/hr with combination of Manipintar Variety, kneading speed of 200 rpm and 24 kg of groundnut seeds. Also, the highest extraction efficiency of 78.59% was achieved with combination of Manipintar Variety, kneading speed of 200 rpm and 12 kg of groundnut seeds. Statistical analysis of the results has established that the use of different quantities and varieties of groundnut seeds on the machine is highly significant on all the performance indicators used. While use of different kneading speeds was found to be highly significant on the extraction rate and extraction efficiency. C
3 |
Author(s):
Galadima, M.S., Muhammad, A. .
Page No : 20-26
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MODELLING OF BINARY SOLVENT EXTRACTION OF CLOVE (SYZYGIUM AROMATICUM) OIL USING RESPONSE SURFACE METHODOLOGY
Abstract
Modelling and optimization of oil yield in binary solvent extraction of clove oil using response surface methodology (RSM) were carried out in this study. The effects of two factors: extraction time and sol-vent/solvent ratio on the oil yield were investigated. A total of 13 experimental runs were generated using central composite design (CCD) in the Design Expert 6.0.6 version. A quadratic model was obtained to predict the oil yield and the Analysis of Variance (ANOVA) showed that the model was significant with P-value <0.0001and R2 value of 0.9962. The statistical model predicted the optimum oil yield to be 30.264% at the optimal condition of time 120 minutes and hexane/ethanol ratio of 1.00. GC-MS analyses of the oil indicated that the main components were eugenol acetate (46.82%), 16-octadecenoic acid methyl ester (16.46%), Hexadecanoic acid methyl ester (7.71%), 1,6,9-Tetradecatriene (6.14%) and stearic acid (3.66%). Physico-chemical properties of the oil indicated that acid value was 23.01 while the iodine value was 20.05 g I2/100 g oil. The oil was dark brown in colour with a pungent clove smell.
4 |
Author(s):
Dangora, N.D., Yusuf, D.D..
Page No : 27-33
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DEVELOPMENT OF A GRAIN DAMAGE MODEL FOR A MOTORIZED STATIONARY MAIZE DEHUSKER SHELLER
Abstract
A Grain damage prediction model was developed for a motorized stationary dehusker sheller. In order to develop an optimization grain damage model for this machine, performance evaluation tests were carried out in two sets, first, to generate data for the development of the models and secondly for validation of the developed models. Each experiment was a factorial design involving four crop and machine variables, speed, S, feed rate, F, concave clearance, C and Moisture content, M, each at three levels, replicated three times. The layout was in a completely randomized block design. Dimensional analysis and the theory of axial threshing were used to develop the model. In evaluation of the Damage model RMSE, Bias, d and SB values of 0.453, 0.121, 0.907 and 0.0144 were computed respectively. These minimal deviation values coupled with high value of 0.907 for the index of agreement, established validity of the prediction. Concave clearance variable has the least sensitivity in the grain damage prediction model.
5 |
Author(s):
Attanda, M.L., Yusuf2, D.D., Muhammad, U.S., Isiaka, M..
Page No : 34-47
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DEVELOPMENT OF SHELLING EFFICIENCY MODEL OF MELON SEED (CITRULLULENATUSKUNTZE) SHELLING MACHINE
Abstract
This study presents the development of a shelling efficiency prediction equation for a melon seed machine shelling process. Analytical approach of dimensional analysis was used in the prediction model development. The shelling rate model parameters of ; moisture content of melon seed, bulk density, feed rate, speed of shelling drum, shelling drum diameter and drum concave clearance of the machine were combined using pie terms theory to form both product and sum components equation of the prediction equations. The two component equations were subjected to evaluation test of bias and root mean square error to determine the appropriate model prediction equation while t-test was used for the significant level of the models developed. Developed prediction equation was validated using sufficient data from extensive testing operation of the shelling machine. A comparison of predicted and experimental data of the machine shelling efficiency showed a good fit with value of coefficient of determination as 0.86.
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Author(s):
Abdulfatah, A.Y., Maikasuwa, A.A., Mahmoud, M.N., Usman, K.R..
Page No : 48-54
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SPATIAL VARIATION OF SOIL PROPERTIES WITHIN BAYERO UNIVERSITY KANO NEW CAMPUS
Abstract
This paper studied the spatial variation of Geotechnical properties of soil samples within Bayero University Kano New Campus. Samples were taken within a radius of 500m across the campus at depths of 1.0m and 1.5m respectively. Laboratory analyses were conducted on the collected soil samples, in accordance with BS 1377: 1990. The results obtained from the laboratory analyses revealed significant variations in index (physical) and engineering properties. There is a percentage variation of 47.1% at 1.0m and 63.7% at 1.5m depths respectively for natural moisture content. Up to 95.6% variation for gravel, 91.9% for sand and 100% for fines. There is up to 18.8% variation in liquid limit, 53.4% in plastic limit, 66% in plasticity index and 21.6% in shrinkage limit. There is a little variation in maximum dry density and optimum moisture content at both depths. For the safe bearing capacity, there is a percentage variation of up to 44.9%. It was therefore concluded that there is the requirement for detailed soil investigation at any given site within the campus before construction work is started.
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Author(s):
Oloyede, Ayopo Abdulkarim, Grace, David.
Page No : 55-73
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ENERGY EFFICIENT BID LEARNING PROCESS IN AN AUCTION BASED COGNITIVE RADIO NETWORK
Abstract
This paper proposes a learning based auction model for cognitive radio network using the concept of Bayesian and Q-learning. A learning process is introduced to aid energy efficiency in an auction based cognitive system. By using Q-learning to learn the bid price, this paper showed that for the learning users, the amount of energy consumed per file sent can be reduced when compared to the non-learning users. Furthermore, to overcome the deficiencies of tra-ditional Q-learning we bias the exploration process with Bayesian learning. This helps the exploration process to converge faster, thereby further reducing the energy consumption by the learning users in the system and the system delay.